As demand for K-12 computer science (CS) education grows, we argue that most students would be best served by CS classes that not only teach computational thinking/programming, but also challenge them to critically analyze the role of technology in society. One of the main barriers to implementing this in K-12 classrooms is a lack of research on how in-service CS teachers can integrate critical pedagogy into their school context and existing curricula. This poster presents results from a study to co-design lessons with current K-12 CS teachers to integrate critical perspectives into their classrooms. Teacher participants participated in a synchronous professional learning series in which we taught them critical computing content drawn from relevant books and frameworks. Following this, we collaborated with the teacher participants to design or modify lessons that engage their students in critical analysis, which the participants then implemented in their classrooms. Teachers were encouraged to include content relevant to their students and the communities they are a part of. We conducted thematic analysis of transcripts from the interviews, professional learning series, and co-design sessions. The resulting eight (8) themes demonstrate the challenges and opportunities inherent in integrating critical perspectives into K-12 computing education. In the long term, results from this work will inform future sociocultural content integration into K-12 CS courses (e.g. ''ethics content'').

This poster examines the commitment of the computer science (CS) education community to equity and justice. By analyzing 146 public pledges from 119 organizations using the Kapor Center's Culturally Responsive-Sustaining Computer Science (CR-SCS) Framework, we assessed focus areas such as racism, inclusive classroom cultures, rigorous curriculum, student voice, community engagement, and diverse experts. Findings show efforts in affirming student identities and community involvement but reveal gaps in addressing racism and recruiting diverse speakers. The results highlight the need for a comprehensive approach to ensure equity and inclusions in CS education. This study provides crucial insights into the current state of CS education and emphasizes the importance of holistic commitments towards justice.

Teachers are increasingly integrating computational thinking (CT) into subject-area learning opportunities with the aim to meet both subject-area and CT learning goals. While prior work has identified CT practices synergistic to subject-area learning, less is published about pedagogical frameworks for instructional practices when integrating CT into content area teaching. This poster presents data from educators (teachers and professional developers) about what they find to be crucial factors for designing and implementing CT integrated lessons. Preliminary analysis indicates educators advocate for twenty practices including creating reflection opportunities, actively using CT vocabulary, opportunities for students to practice CT skills, meaningful real-world connections, utilizing scaffolding strategies, explicitly introducing CT practices, clear connections between CT and curricular content, using multiple modalities, and encouraging student discourse.

Ethnocomputing describes the study of computational ideas and thinking as they appear in the artifacts, epistemologies, designs, and practices of temporally and spatially situated communities (e.g., from computational scientists to textile artisans). It is also about how such communities embed their beliefs and values within computational artifacts. One outcome of ethnocomputing research is the demonstration of how Indigenous and diasporic communities have dynamic computational histories and innovations that are relevant to computer science and computer science education today. From lessons on e-textiles and Native American botanical knowledge to visual programming environments that reveal the algorithms of cornrow braiding in the Black diaspora, this has allowed for anti-racist challenges to white supremacist myths of primitivism in primary and secondary computer science education. While there are studies about how ethnocomputing tools and lessons shape children's attitudes toward and knowledge of computing, there is no research on what computer science teachers think about one of ethnocomputing's foundational assumptions: computational ideas and thinking are embedded within Indigenous and vernacular artifacts, epistemologies, designs, and practices. This paper reports findings from interviews with 14 K12 computer science teachers who had been exposed to ethnocomputing educational technologies and activities. From our qualitative analyses, we found that most (n=12) teachers believed that Indigenous and/or vernacular artisans think computationally. We detail their lines of reasoning before turning toward teachers who had ambivalent (n=1) or negative (n=1) positions about this assumption of ethnocomputing research. We discuss the implications of these findings for anti-racist K12 computer science teacher professional development.

Justice-centered computing scholarship has made significant efforts in broadening the participation of underrepresented groups, particularly along the lines of race, gender, and class. However, the role of immigrant students' national identities in these efforts have been largely ignored. In this lightning talk, we present preliminary findings from an ongoing study that explores the perspectives of computer science teachers - who work in classrooms with students from diverse national backgrounds - about national identity and national culture. The study examines how these computer science teachers understand the role of students' national identities and national cultures within the CS classroom. Our study was guided by the following research question: how do computer science teachers understand the national identities and national cultures of their students? We focus on three findings: first, the role that teachers place on national identity and national culture in students' sense of self, second, the ways in which teachers understand how national culture intersects with students' family cultures and age groups, and third, the influence of national identity and national culture on students' learning experiences within the classroom. These insights provide nuanced perspectives to broadening participation efforts in computer science education.

With over 22 million students enrolled in PreK-5 grades in the United States alone, we recognize that this is an important opportunity to bring computer science (CS) education to millions more students than who have traditionally had access. It also presents a unique opportunity to embrace teaching computer science in these early grades that is highly inclusive, engaging, and even blended with traditional subjects taught in these early years. In this panel, we bring together a collection of experts in the PreK-5 field, including researchers, a curriculum designer, and teachers, to discuss promising practices for including CS instruction in the PreK-5th grades, focusing in particular on PreK-2nd grades. The intended audience for this panel includes researchers and practitioners who are interested in CS in the early elementary and early childhood years. This topic is highly relevant to the SIGCSE community since it brings together teachers, curriculum designers, and researcher perspectives into a shared space to highlight the ways schools, teachers, and researchers can think about successfully adding computer science into young children's education.

The session will present the final report of an NSF sponsored workshop tasked with creating a vision for computing education for the next 15 years. Within several broad themes identified, the panelists were asked to probe further into where the field should be heading and what difficult questions we need to tackle. We will use the final report as a basis for discussion with the attendees and ask them the same hard questions we asked ourselves when writing this report to see how these questions shape their views of where computing education needs to be in the next 15 years.

As demand for K-12 computer science (CS) education grows, we argue that most students would be best served by CS classes that not only teach computational thinking/programming, but also challenge them to critically analyze the role of technology in society. One of the main barriers to implementing this into K-12 classrooms is a lack of research on how in-service CS teachers can integrate critical pedagogy into their school context and existing curricula. This lightning talk presents a proposed method to co-design lessons with current K-12 CS teachers to integrate critical perspectives into their classrooms. Teacher participants will join a synchronous summer professional development where we will teach them critical computing content drawn from relevant books and frameworks, and collaborate with them to design or modify lessons that will engage their students in critical analysis. Teachers will be encouraged to include content relevant to their communities. For example, a teacher in Detroit might teach facial recognition in the context of continued use of the technology by police, despite wrongful arrests. Results from this work will inform future sociocultural content integration into K-12 CS courses (e.g. "ethics content"). Feedback from the audience will be used to improve the methods and literature review of the study.

Neoliberal capitalism - the favoring of privatization, marketization, and deregulation of public resources - is hegemonic in education. It shapes our institutions and everyday life, including educational practices. The increasing push for market driven computing curriculum and large tech companies' involvement in research grants and educational programs are some examples of neoliberal influences in CS education. It is not only industry and industry-backed not-for-profits such as Code.org that reify neoliberal agendas, but in many cases, our very own communities, educational institutions, and curricula. Thus, a critical and reflective examination of our educational practices is necessary. In this Birds-of-a-Feather (BoF) session, we aim to conduct reflections and discussions on the role and influence of neoliberal capitalism in computing education. We will explore 1) the influence of deregulation, 2) public-private partnerships, 3) state-subsidized corporate wealth accumulation, and 4) centralization on pedagogy, research, and academic "success". We will discover reflective questions and practices that could help us critically examine our roles and responsibilities as computing educators and professionals. Eventually, we hope to begin a larger conversation and form a community to develop collective strategies and pedagogical ideologies to resist neoliberal influences, reimagine alternatives, and repair damages caused by neoliberal computing education.

In response to the enrollment surge that started in many CS depart- ments around 2006, the Computing Research Association published a report on "Generation CS", which named a pervasive theme in computing education: more and a greater diversity of students are seeking computing education, even if not as traditional CS ma- jors. However, our curricula and departments have stayed much the same. We still mostly prepare students for software develop- ment jobs in the technology industry, while we rarely identify the damage that same industry has caused in our democratic societies. How do we do better? How do we change to meet the needs of a changing society? What strategies should we apply? We know that large-scale change will require structural shifts, but such shifts are likely to be slow and expensive, whereas smaller, "boots on the ground" initiatives can positively impact individuals but do little to change the systems that underlie the deeper-seated problems in computing. Navigating this paradox is imperative to our success as a field. Our panel will address the big questions about how to make structural changes in computing education in order to meet the greater needs of Generation CS.

To address racial and gender inequality in K12 STEM and computer science education, there needs to be mutli-pronged approach. In addition to the needed work for curricula that is culturally responsive and sustaining, inclusive of all student group, and positively welcomes the identities of historically marginalized people groups, K12 computer science teachers need to be equipped with the training and tools to implement the curricula, pedagogy, and instruction to mitigate the racial and gender gaps in K12 computer science education.

As issues of ethics, criticality, and social impact become more important in computer science, so does the need to teach them in CS classes. Despite the recent growth of academic writing around ethics in CS and a push for teaching ethics in post-secondary CS classes, the K-12 space has largely been ignored. To explore integrating ethics into K-12 CS classes, we interviewed a diverse group of current US K-12 CS teachers and conducted a thematic analysis to understand how they conceptualize ethics in CS and see potential opportunities and barriers to ethics integration in their classroom context. We found that teachers initially associated ethics with digital citizenship and gender/race imbalances, but were largely unfamiliar with issues of algorithmic bias, injustice, and techno-solutionism. After being introduced to these ideas and presented with examples, the teachers started to broaden their perspective of CS ethics. However, there are still barriers to teachers integrating ethics into their classroom (e.g. curriculum, time constraints). We discuss potential future pathways for K-12 CS ethics including through integrating ethics into digital citizenship.

Employers regularly list teamwork as one of the most desirable skills they are seeking in college graduates. This paper describes a study about the effect of teamwork on student learning and classroom culture in a CS1 college class. In Fall 2021, an experienced college professor taught with POGIL for the first time in three sections of CS1. In two sections, students completed the POGIL activities in teams. In the third section, students completed the same POGIL activities individually. This study was then repeated in Spring 2022. In the fall semester, we observed a noticeable effect on classroom culture but no differences in student learning. In the spring semester, students in the sections with POGIL teams performed better on quizzes and programming assignments than those in the section where students worked individually. We discuss the implications of these results on collaborative learning in CS courses and the importance of student teams for faculty adopting POGIL.

Computing has been historically taught as neutral and devoid of any connection with societies. But more recently, technical tools are taking center stage at societal problem solving, influencing policies and practices around issues such as surveillance, privacy, and algorithmic bias. In this sociopolitical moment, people across different efforts within K-12 computing education are calling for integration of computing with social sciences to center implications of technologies on peoples, communities, and societies. There are multiple facets to these efforts: studying K-12 student engagement with critical content to preparing K-12 educators and ecosystems, developing pedagogical frameworks, and redesigning existing high school computing program to center justice. This panel will present a broad range of efforts towards critical introduction of computing within K-12 settings. While briefly introducing themselves and their work, each panelist will answer the questions: (a) How does your work and experiences address critical computing education? (b) What are some barriers that you have encountered? And (c) How have you addressed these concerns within your designs? Overall, the panel will open the space for discussing, highlighting, and learning from this set of diverse and synergetic critical computing efforts within K-12 computing education.

Efforts in the United States to broaden the participation of racial and ethnic minorities in K12 computer science (CS) education often focus on the need for children to change themselves to meet the standards and norms of traditional computing education. Less attention has been paid to how CS education itself might change and adapt to cultural contexts and locations that children already participate in and find of value. In this paper, we describe efforts to change the shape and culture of CS education by designing and implementing it in and for a youth boxing gym in an African American community. We report findings from a boxing inspired CS curriculum that was designed in collaboration with boxing coaches, mentors, and academic staff members at the gym. It was piloted over the course of two six-hour workshops with 15 middle and high school age children. We focused on two issues that are relevant to broadening participation and reshaping the culture of CS education: (1) how the curriculum changed children's perceptions of CS and (2) the creative adaptations that children made to the curricular content and materials. An analysis of pre- and post-surveys using a nonparametric test showed significant positive changes in children's responses to the constructs of self-confidence and expression with CS. Vignettes of children appropriating and personalizing technologies from the workshops are used to unpack these findings. We end with a discussion about the implications of these findings for culture-based CS education in both school and community contexts.

Across the globe, Computer Science Education has grown tremendously over the past decade to teach primary and secondary students computing ideas and tools. From integrating computational thinking in disciplines to teaching computer science as a stand alone subject, models for teacher preparation range from one and done professional learning workshops to full certificate and licensure programs. The group will focus on providing a landscape of how CS teachers are prepared academically in various countries and make evidence-based recommendations for how teachers should be educated to develop knowledge and skill to teach computer sci- ence. The working group will also discuss how to develop these knowledge systems while promoting instruction that is equitable and centers students in the classroom. In addition, the working group will focus on new directions in computing education (such as, artificial intelligence and machine learning) and their implica- tions for teacher preparation. We will bring together a group of international computer science education scholars who have been engaged in teacher preparation. In addition to what knowledge teachers need to teach CS, we will also focus on how the field is preparing teachers to think critically about AI/ML and the role of computer science in the design of technology tools to achieve goals while mitigating potential societal harms.

In recent years, there has been a growing awareness of the need for computer science education opportunities and particularly for engaging students in computational thinking ideas and practices to help them understand how computing influences our world. At its core, computational thinking (CT) is seen as understanding how computational practices (such as, abstraction) and tools (such as modeling software) can be used to explore phenomena, solve problems, and influence our lives and society. The push for CT integration has called for preparing future educators to learn CT practices and tools through stand-alone courses and within the context of disciplinary pedagogy/methods courses. However, there are few instruments that measure pre-service teachers' attitudes towards computational thinking and its role in formal schooling. In this study, we developed and validated an instrument to measure pre-service teachers' attitudes towards CT, its role in students' lives, and their own self-efficacy to incorporate CT into their teaching. We report results from a principal components factor analysis on survey responses from 260 pre-service teachers to identify patterns and reduce the number of dimensions of comparison in the analysis. We discuss how pre-service teacher conceptions have implications for preparing future teachers to integrate computational thinking into their instruction.

In this poster, we will present approaches and associated design principles for integrating computational thinking (CT) into middle school Social Studies, Arts, and Language Arts instruction to enhance disciplinary learning. We used four steps to identify these approaches and design principles: (1) co-design with teachers and experts in computer science and CT education to ideate CT-integrated lessons; (2) identifying initial design principles based on the ideated lessons; (3) consultation with subject matter experts; and (4) conducting a Delphi study with pedagogical experts (e.g., teachers, curriculum writers, teacher educators) to examine the clarity, feasibility and potential impact of the design principles. The process led to three broad approaches to integrate CT into Social Studies instruction that included 14 design principles, three for Arts with 16 design principles, and four for Language Arts with 12 design principles.

The session will present an overview of findings of a recently funded NSF workshop that set out to examine the pressing issues for computing education research for the next 15 years. Based on dialogs for scholars working in this area, the workshop participants developed a series of themes and topics that they felt should become the focus of computing education research efforts for the next 15 years. Main themes that emerged and will be discussed in this session include: diversity, equity, inclusion, ethics, broadening participation, teaching, learning, K-12, research to practice, computing's connection to other fields, and computing education research disciplinary issues. The session will focus on interesting research questions from each of these areas that are ripe to be explored as well as enablers and blockers to the progress of this work.

In K-12 education, nearly all efforts focused on expanding computer science education center on the induction of new computer science teachers, with very little attention given to support the ongoing needs of experienced computer science teachers. More seasoned teachers benefit from deepening their content knowledge, pedagogical practices, and knowledge and capacity to provide equitable and inclusive learning experiences that results in students feeling a sense of belonging in computer science. This panel will discuss the needs of experienced CS teachers from a variety of perspectives, including teacher education researchers, professional development leaders, and high school practitioners and teacher facilitators. The panel will collectively outline a research and practice agenda that focuses on supporting, retaining, and further developing experienced teachers through expanded professional development, leadership opportunities, and community for CS teachers.

To encourage and support faculty to adopt active learning pedagogies, we need to understand: (1) what faculty perceive as the challenges and benefits of adoption; and (2) how professional development and support affect faculty adoption. This paper describes a project to provide professional development and support for faculty planning to adopt POGIL in their introductory CS classes. Process Oriented Guided Inquiry Learning (POGIL) is an evidence-based, student-centered pedagogy that focuses on developing both content knowledge and process skills. Using workshop evaluations, interviews, and an end-of-term survey, we found that participating faculty appreciated the additional training, learning materials, and mentoring. They reported that they implemented most key elements of POGIL and that POGIL enhanced student engagement and learning. Key challenges include the time required to complete in-class activities, cover course content, and prepare for activities. These results should help to improve professional development for faculty who want to adopt evidence-based strategies to improve student outcomes.

For the past ten years, computer science instructors have adopted Process Oriented Guided Inquiry Learning (POGIL). Other STEM disciplines have shown conclusively that POGIL impacts student learning and knowledge retention. However, most research about POGIL in computer science has focused on perceptions and experiences, not learning outcomes. In this study, we examined the influence of POGIL on student learning in CS1. We collected data from all sections of CS1 at the same institution. Four of the faculty implemented POGIL, and three taught with other active methods. The learning data included pre and post assessments, midterm and final exams, and a retention test at the beginning of the next course. Students also completed three surveys about their prior programming experience, sense of belonging, and perceptions of teamwork. We used multiple regression to analyze the relationship between the survey data and learning outcomes. Our results show that students in the POGIL sections outperformed students in the other sections. POGIL students scored higher on the post-test, and a higher proportion of them met the grade requirement to progress to the next course. After the five-week winter break, POGIL students had higher and more consistent scores on the retention test. These results provide evidence that POGIL can be very effective as an instructional technique in computer science.

Women's participation rates in the Computer Science (CS) field are alarmingly lower than men's in K-12 and higher education as well as in the workforce. Research has been done to explore when young women's potential interest in the field typically develops, but these studies primarily target the high school and undergraduate levels. This mixed methods study examined middle school students' perceptions of computer scientists' looks and character traits, students' sense of belonging in the CS community, and the relationship between stereotype adoption, gender, and sense of belonging. Ninety-five (95) participants depicted computer scientists through drawing and a written explanation of their depiction. A subset of participants also had their sense of belonging in CS measured through the CS Sense of Belongingness Scale. A 2 (gender) x 2 (stereotype adoption) ANOVA was used to examine the relationships between students' perceptions, their sense of belonging, and gender. Results from the study suggest that there were significant differences between girls' and boys' perceptions of computer scientists' appearance; however, there were no differences in their perceptions of computer scientists' character traits. There were also no differences in students' sense of belonging based on the stereotype adoption levels and gender. Despite its limited sample size, this study provides insights on how middle school students think about computer scientists and the stereotypes they hold.

While computational thinking has gained popularity in K-12 schools to increase access to computing tools and practices, there is still limited understanding on how to broaden participation of students with disabilities in computational thinking (CT). One approach to increasing access to computing to students with disabilities is to educate future special education teachers to bring CT into their instruction. This study examined the influence of integrating CT into assistive technology course for special education pre-service teachers. Our results suggest that integrating CT into special educa- tion teacher preparation coursework can have a positive impact on how pre-service teachers see the value of bringing computational practices to students with disabilities.

Computer science education (CSEd) is a growing interdisciplinary area that continues to gain momentum from students, researchers, and educators. Yet, there are few formal programs or degree options for students interested in pursuing graduate work in CSEd. This article explores the existing state of CSEd in the United States (U.S.) through semi-structured interviews with ( n = 15) faculty engaged in CSEd research. Thematic coding of the transcripts revealed the complexities involved in the development of formal programs, the distinct considerations for faculty, and the value of having strong ties to both computer science and education. The themes described positive aspects of support and cohesion within the larger community and opportunities to expand knowledge across fields. Applying Cornell and Parker’s principles of interdisciplinary science to the field of CSEd, we provide recommendations for ways forward and discuss the potential impact on institutional structures, research capacity, individual and group identities, and teaching and learning. The findings from this investigation not only inform on the present state of CSEd in the U.S., but also offer guidance for CSEd-focused graduate programs.

Recent years have seen increased focus on integrating Computational Thinking (CT) across subject areas in lieu of treating it as a standalone subject. Over the course of two years, we focused on teacher development in a large city school system via summer workshops that brought in-service and pre-service teachers together to co-create integrated CT lessons. In this experience report, we will describe the workshop design and share the perspectives of the participating K-5 teachers. One particular area of focus of the workshop was integrating 'plugged' or technology-based computing examples for the teachers. Further, we engaged the teachers with a discussion of the role of CT in promoting equity for students and demonstrated ways in which student cultural experiences could be activated through creative computing. Specific outcomes of the work included increased confidence and value in CT vocabulary usage, ideas to infuse existing curriculum with CT ideas, and teacher belief that CT could be used as a "gateway" for learning CS. We make recommendations for future efforts to include CT in pre-service teacher preparation.

In this poster, we will present the initial results of a meta-aggregation study that synthesizes qualitative evidence to identify the charac- teristics of effective in-service teacher professional development programs (TPD) around computational thinking (CT) integration in K-12. In addition, we will discuss the importance of these char- acteristics in supporting teachers. We identified four synthesized findings representing the key characteristics of effective TPDs for CT integration in K-12 (e.g., improving teacher capacity in CT in- tegration, creating meaningful learning experiences, establishing research-practice partnership, and providing continuous and sus- tainable support).

Prior research has shown that a sense of belonging is very important for students to continue in their field of study. This is particularly true for minoritized students in introductory CS courses. The methods used so far to study sense of belonging in CS have been qualitative or have used a small number of survey items. In this paper, we validate a large 30-item survey originally developed for Mathematics. We collected data from 21 institutions, with 30 faculty and 1165 survey responses. We present a factor analysis for the survey to highlight how it measures factors like 'Membership', 'Acceptance', 'Affect', 'Trust' and 'Desire to Fade'. We measured the students' sense of belonging using the survey and found that it correlates with their learning and their interest to pursue more CS courses. These correlations were nuanced based on students' gender, race, and the type of learning environment. We found that for minoritized students in particular, the interest to pursue CS courses was more correlated with their sense of belonging. A type of learning environment we examined was Process Oriented Guided Inquiry Learning (POGIL). We studied the differences in sense of belonging between POGIL and non-POGIL classrooms. Although we did not find a significant difference in overall sense of belonging at the factor level, we did find significant differences when we examined at the item level. These results shed light about nuances in students' sense of belonging in CS POGIL classrooms when compared to other approaches.

This study examines the self-efficacy of prospective computer science teachers and the background factors that may be related to differences in their self-efficacy. The self-efficacy profiles of teachers were examined using cluster analysis, and three self-efficacy profiles were established. Then the differences between clusters were examined with respect to several categorical variables regarding their teaching background experiences. The results of this study show that teachers' self-efficacy for teaching computer science varies with their academic background, but not with other background characteristics like their amount of teaching experience or prior experience level with CS.

Collaborative learning actively engages students in the learning process while developing professional skills that employers seek. Approaches such as Pair Programming and Peer Instruction have been shown to improve student outcomes in computer science. Process Oriented Guided Inquiry Learning (POGIL) is another col- laborative learning approach that aims to develop students' mastery of discipline-specific concepts as well as 'process skills' like com- munication, teamwork, and critical thinking. This paper examines students' perceptions of their content learning and process skills in courses that recently switched to POGIL. We explore the re- lationship between those perceptions, self-efficacy, and learning performance. Our results show that students have positive views about their teamwork, developing skills to work with others, and thinking through a problem. However, self-efficacy is the only sig- nificant predictor of their learning. We discuss the implications of these results for using POGIL and other collaborative learning in CS courses, and identify directions for future work.

Research has repeatedly shown self-efficacy to be associated with course outcomes in CS and across other fields. CS education research has documented this and has developed CS-specific self-efficacy measurement instruments, but to date there have been only a few studies examining interventions intended to improve students’ self-efficacy in CS, and several types of self-efficacy interventions suggested by previous research remain to be tested in CS. This study attempts to address this lack of research by reporting on the results of a trial intervention intended to improve students’ self-efficacy in an introductory programming course. Students were recruited to complete a self-evaluation task, which previous research has suggested could have a beneficial impact on self-efficacy, which should in turn have a beneficial impact on course performance. Participating students’ course outcomes and self-efficacy were compared with those of the students who did not complete the self-evaluation task, using propensity score weighting adjustments to control for differences between the groups on entering characteristics and prior values of self-efficacy and course outcomes. We found that, whereas there was only marginal evidence for the self-evaluation intervention having a direct effect on self-efficacy, students who completed the self-evaluation task had significantly higher project scores during the weeks they were asked to complete it, compared to the students who did not participate. These findings suggest that there are potential benefits to incorporating self-evaluation tasks into introductory CS courses, although perhaps not by virtue of directly influencing self-efficacy.

The increasing role of computation in today's society requires us to go beyond computer science courses to integrating computational tools and practices within disciplinary contexts. However, we know little about what integration looks like in primary, secondary, and university classrooms. In this panel, we share perspectives on the importance of developing knowledge of computation in a digitized world and how it could be integrated within disciplinary context. In particular, we will discuss what embedding computation looks like at the elementary, secondary, and university level and how it can support disciplinary learning.

Policymakers believe that preparing all students from the earliest grades to high school for a new future of STEM+Computing (STEM+C) integration involves teaching them not only the science and math central to these areas, but also how computational thinking is integral to STEM disciplines. This panel brings together four researchers who focus on research and development of interdisciplinary approaches to the integration of computing within STEM teaching and learning for preK-12 students. They will share the most impactful, practical, and promising approaches to STEM+C integration, their pros and cons, challenges, and key insights to successful STEM+C integration at all grade levels.

Opportunities for training CS K-12 pre-service and in-service teachers, research in CS Education, and career pathways for PhDs/EdDs in CS education are happening, but often in an uncoordinated way. We advocate that now is the right time for CS and Education to collaborate on developing new joint degree programs in Computer Science Education and to explore joint faculty appointments. High undergraduate enrollment in computing programs and the increasing interest in CS courses from non-majors represent a unique opportunity for starting successful programs. As more of CS undergraduates are undergraduate TAs and see teaching and learning from a non-learner perspective, their interest in education has also increased. The growing interest in CS education, including the need for effecting CS teaching at both K-12 and the undergraduate level, provide interesting job opportunities for CS education researchers. As CS departments develop new undergraduate degree programs and scale class sizes, research on questions like How do we teach effectively computing to different audiences? How can we assess CS learning? What are culturally responsive pedagogies? is important. To answer many of these and related questions, CS departments should be actively engaged in CS Education research, from training graduate students in interdisciplinary programs to research programs. This BOF will provide a platform for the discussion on what such graduate programs - from certificate to a PhD - can and should look like, what challenges exist to creating them, and how students with different backgrounds should get trained in the relevant foundations of CS and Education.

As computer science is moving into K-12 education, most efforts have focused on getting new teachers into computer science or integrating computing within STEM topics. But one aspect that has received less attention, if any, is the continued professional development of experienced CS teachers. We know little about the particular learning needs of experienced CS teachers, knowledge that will be critical as the CS teaching force expands significantly in coming years. In this panel, we address this knowledge gap from the perspective of teacher education research and professional development-what we need to know about deepening teachers' pedagogical practices and content knowledge-an understanding that will be instrumental for retaining and enriching teachers in CS education.

The 32 chapters of the 2019 Cambridge Handbook of Computing Education Research synthesize the existing research in computing education and propose new directions for future research. An author from each chapter will summarize their chapter with auto-advancing slides. Attendees will be introduced to the breadth of content in the new handbook and can identify chapters of interest. This fits uniquely as a special session, and will likely be informative, inspiring, and overwhelming.

Courses designed for Massive Open Online Courseware (MOOC)platforms provide learners worldwide with extensive learning opportunities. Previous research has explored learner motivation in MOOC courses using self-regulated learning (SRL) theory. How-ever; the majority of this work has focused on adults and we know little about how high school learners use SRL strategies. This paper explores self-regulated learning differences between high school students enrolled in traditional face-to-face and MOOC Advanced Placement Computer Science A courses. We found significant differences in student help seeking abilities between the two courses, but not in other SRL behaviors (such as, metacognition, effort regulation, etc.). In addition, help seeking was the only SRL strategy that was significantly related to MOOC students' grades on programming tasks. We discuss implications for designing MOOC courses for younger learners and directions for future research to disentangle the role of MOOC environment and motivation in influencing student outcome

The competitive market of mobile apps requires app developers to consider the users' feedback frequently. This feedback, when comes from different resources, e.g. App Stores and Twitter, will provide a broader picture of the state of the app, as the users discuss different topics on each platform. Automated tools are developed to filter the informative comments for app developers. However, to integrate the feedbacks from different platforms, one should evaluate the similarities and/or differences of the text from each one. Different meaning of the words in various context, makes this evaluation a challenging task for automated processes. For example, Request night theme and Add dark mode are two comments that are requesting the same feature. This similarity cannot be identified automatically if the semantics of the words are not embedded in the analysis. In this paper, we propose a new framework to analyze the users' feedback by embedding their semantics. As a case study, we investigate whether our approach can identify the similar/different comments from Google Play Store and Twitter, in the two well studied classes of bug reports and feature requests from literature. The initial results, validated by expert evaluation and statistical analysis, shows that this framework can automatically measure the semantic differences among users' comments in both groups. The framework can be used to build intelligent tools to integrate the users' feedback from other platforms, as well as providing ways to analyze the reviews in more detail automatically.

The representation of women in computer science (CS) is low in the United States and has been declining over the past few decades. Prior research has demonstrated that educators play an important role in increasing gender diversity. Not much, however, is known about their views regarding gender diversity in CS. Educators are often isolated as the only ones teaching CS in their schools, with limited opportunity to converse with each other about the underrepresentation of women in CS and other issues facing the field. Thus, to better understand educators rq questions and concerns about gender diversity, we conducted a qualitative exploratory study within an online discussion forum, Stack Exchange for CS educators. The conversations gave us insights into gender diversity issues that the forum members were interested in, such as enrollment, retention, and roles of teachers. We also analyzed the lenses through which the forum members spoke about gender representation. Results from this study suggest that researchers need to continue to examine educator perceptions so that we can design appropriate online teacher communities, teacher education courses, and professional development workshops to address equity and gender diversity issues in CS.

Introductory computer science courses face multiple challenges, including a broad range of content, diverse teaching methods, and the need to help students develop skills such as problem solving, critical thinking, and teamwork. One evidence-based approach to address these challenges is Process Oriented Guided Inquiry Learning (POGIL), in which student teams work on classroom activities specifically designed to help them construct understanding and develop key skills. While POGIL has been widely used and studied in Chemistry and other STEM fields, much less is known about how it is used in Computer Science. In this study, we examined how faculty adopt POGIL for the first time in introductory CS classrooms. Using qualitative in-depth interviews, we investigated why faculty chose to adopt POGIL and their concerns about using it. Our results suggest that faculty motivations to use POGIL centered around improving student outcomes, including their learning and engagement. However, faculty also had concerns about using POGIL, which ranged from how POGIL impacts the curriculum to logistical and institutional barriers. We discuss the implications of these findings with respect to faculty development and active learning pedagogies.

The current efforts to expand computer science (CS) education in K-12 schools, such as the “CS for All” initiative, highlight the need for all students to get an opportunity to study computing. However, as recent research has shown, diversity in computing at the K-12 level remains problematic, and additional research is needed to look at how computer science learning environments can impact minority student interest and retention in CS. In this article, we report results from an in-depth qualitative study of high school computer science teachers’ perspective on barriers to increasing diversity in their classes. Based on teachers’ experiences, we provide practical recommendations on how to encourage equitable learning environments in K-12 computer science courses.

Computer science education efforts are expanding across the globe to equip students with the necessary computing skills for today’s digital world. However, preparing students to become literate in computing activities requires the training of tens of thousands of teachers in computer science. The discrepancy between student needs and teacher preparation in computer science has raised questions of quality teachers, particularly for teachers who do not possess adequate content or pedagogical knowledge to teach computer science efficiently. To address this issue, we designed an instrument to measure knowledge needed to teach computer science (i.e., computer science pedagogical content knowledge). Results exhibited that our instrument measured aspects of teachers’ computer science pedagogical content knowledge; however, teachers’ prior background in teaching did not influence their performance. We discuss implications for future research and practice.

Previous research has found that programming assignments can produce strong emotional reactions in introductory programming students. These emotional reactions often have to do with the frustration of dealing with difficulties and how hard it can be to overcome problems. Not only are these emotional reactions powerful in and of themselves, they have also been shown to induce students to make self-efficacy judgments, which can in turn cause adaptive or maladaptive behaviors, depending on the valence of the judgment. These results have been found in previous qualitative research in programming, however, to date no one has done a larger scale quantitative examination of emotional reactions in introductory programming students. Furthermore, no one has tried to connect these emotional reactions systematically to student learning outcomes. Therefore, this study reports on the pilot use of a basic emotional reactions survey with a large class of undergraduate introductory programming students. Preliminary results are presented on how these emotional reactions affect students' course outcomes over the short and longer term.

The problem of the lack of rigor in CS education research has frequently been discussed and examined. Previous reviews of the literature have examined rigor on both theoretical and methodological dimensions, among others. These reviews have also looked at differences in indicators of rigor between conference proceedings and journal publications. However, to date there is no comprehensive review that has examined the intersection of methodological and theoretical quality.

Previous research in computer science education has demonstrated the importance of motivation for success in introductory programming. Theoretical constructs from self-regulated learning theory (SRL), which integrates several different types of metacognitive processes, as well as motivational constructs, have proved to be important predictors of success in most academic disciplines. These individual components of self-regulated learning (e.g., self-efficacy, metacognitive strategies) interact in complex ways to influence students' affective states and behaviors, which in turn influence learning outcomes. These elements have been previously examined individually in novice programmers, but we do not have a comprehensive understanding of how SRL constructs interact to influence learning to program. This paper reports on a study that examined the interaction of self-efficacy, intrinsic and extrinsic goal orientations, and metacognitive strategies and their impact on student performance in a CS1 course. We also report on significant gender differences in the relationships between SRL constructs and learning outcomes. We found that student performance had the expected motivational and SRL precursors, but the interactions between these constructs revealed some unexpected relationships. Furthermore, we found that females' self-efficacy had a different connection to programming performance than that of their male peers. Further research on success in introductory programming should take account of the unique and complex relationship between SRL and student success, as well as gender differences in these relationships that are specific to CS.

This paper presents an analysis of CS faculty perceptions of the benefits of POGIL, the obstacles to POGIL adoption, and opportunities for professional development. Participants strongly agreed that with POGIL, students are more engaged and active, develop communication and teamwork skills, and have better learning outcomes. The largest perceived obstacle was lack of preparation time; other obstacles included availability of relevant POGIL activities and pressure to cover more content. Participants expressed a desire for further training and mentoring beyond workshops. Our data analysis also considers bivariate associations and interactions. The results should help to improve professional development for CS faculty adopting evidence-based strategies, and thereby help more CS students to be successful.

Previous research has suggested that cognitive tests, including instruments seeking to measure problem solving, are significant predictors of students' programming performance. This paper seeks to expand upon this previous research by using a more theoretically grounded approach to measuring problem solving as a means of predicting performance in an introductory undergraduate programming course. Programming course performance has typically been measured by overall course grades; however, in this paper we used a more fine-grained approach to measuring student programming performance. Specifically, we utilized different types of course assignments (projects and tests) to measure programming outcomes. Results from this study indicate that problem solving ability significantly correlates with performance on programming assignments, but does not correlate with performance on multiple-choice exams.

In both flipped classroom settings and distance learning, educational content is typically delivered via video lectures that students watch alone. While flipped classrooms typically provide students with opportunities for social interaction that feature active learning, online learners are not typically afforded these opportunities. Cooperative learning techniques like Lightweight Teams provide social, collaborative learning opportunities to students in flipped classrooms but extending these techniques to distance learning settings is not straightforward. In this paper, we present our experiences with online, distributed Lightweight Teams. We present an in-the-wild study that compares learning outcomes and student preferences between co-located and distributed Lightweight Teams against the base case of individual learning. Our results show that while there are no significant learning differences between the two team conditions and the individual condition, students significantly prefer the team conditions.

This workshop will provide CS educators with tools to conduct educational research. Primary objectives of this workshop are: (1) learn basic principles of research design; (2) learn about various types of research designs: qualitative vs. quantitative; experimental vs. quasi-experimental; case studies, survey; and (3) to practice designing research. This workshop will help participants make informed decisions when faced with limitations of educational research and collect empirical evidence about what works in the classroom. In addition, we will also discuss how to develop robust student outcome measures, such as surveys and tests. The workshop will be beneficial to participants who have not yet done all of these activities as well as those who have some background in educational research. Participants will be provided with material on research designs.

Active learning is important in computer science education, where students often don't have enough opportunities for social learning and development of soft skills. Flipped classrooms can provide social interaction through approaches such as lightweight teams [23], where students collaborate during class in low-stakes peer learning. These teams scaffold positive interdependence [17] by removing high-stakes assignments that heavily impact student's grades.

This workshop will provide CS educators with tools to conduct educational research. Primary objectives of this workshop are: (1) learn basic principles of research design; (2) learn about various types of research designs: qualitative vs. quantitative; experimental vs. quasi-experimental; case studies, survey; and (3) to practice designing research. This workshop will help participants make informed decisions when faced with limitations of educational research and collect empirical evidence about what works in the classroom. In addition, we will also discuss how to develop robust student outcome measures, such as surveys and tests. The workshop will be beneficial to participants who have not yet done all of these activities as well as those who have some background in educational research. Participants will be provided with material on research designs.

Computational thinking (CT) is broadly defined as the mental activity for abstracting problems and formulating solutions that can be automated. In an increasingly information-based society, CT is becoming an essential skill for everyone. To ensure that students develop this ability at the K-12 level, it is important to provide teachers with an adequate knowledge about CT and how to incorporate it into their teaching. This article describes a study on designing and introducing computational thinking modules and assessing their impact on preservice teachers’ understanding of CT concepts, as well as their attitude towards computing. Results demonstrate that introducing computational thinking into education courses can effectively influence preservice teachers’ understanding of CT concepts.

This workshop will provide CS educators with tools to conduct educational research. Primary objectives of this workshop are: (1) learn basic principles of educational research; (2) learn about educational research designs: qualitative vs. quantitative; experimental vs. quasi-experimental; case studies, survey; and (3) to practice designing research. This workshop will help participants make informed decisions when faced with limitations of educational research and collect empirical evidence about what works in the classroom. In addition, we will also discuss how to develop robust student outcome measures, such as surveys and tests.

As computational thinking becomes a fundamental skill for the 21st century, K-12 teachers should be exposed to computing principles. This paper describes the implementation and evaluation of a computational thinking module in a required course for elementary and secondary education majors. We summarize the results from open-ended and multiple-choice questionnaires given both before and after the module to assess the students' attitudes toward and understanding of computational thinking. The results suggest that given relevant information about computational thinking, education students' attitudes toward computer science becomes more favorable and they will be more likely to integrate computing principles in their future teaching.